samsung SM-S938U
Geekbench ML Score
1985
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 07 2025 01:07 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938U |
| Model ID | samsung SM-S938U |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1188
222.3 IPS |
|
|
Image Classification (F16)
|
100% |
1251
234.1 IPS |
|
|
Image Classification (I8)
|
97% |
1431
267.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1638
27.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1669
27.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1747
29.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
2203
2.67 IPS |
|
|
Pose Estimation (F16)
|
100% |
2159
2.61 IPS |
|
|
Pose Estimation (I8)
|
100% |
8542
10.3 IPS |
|
|
Object Detection (F32)
|
100% |
1191
88.9 IPS |
|
|
Object Detection (F16)
|
100% |
1226
91.5 IPS |
|
|
Object Detection (I8)
|
61% |
1887
140.9 IPS |
|
|
Face Detection (F32)
|
100% |
2465
29.3 IPS |
|
|
Face Detection (F16)
|
100% |
2430
28.9 IPS |
|
|
Face Detection (I8)
|
86% |
4266
50.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
2256
17.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
2256
17.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
4272
33.1 IPS |
|
|
Style Transfer (F32)
|
100% |
3485
4.58 IPS |
|
|
Style Transfer (F16)
|
100% |
3533
4.65 IPS |
|
|
Style Transfer (I8)
|
98% |
9782
12.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1389
49.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1330
47.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4038
144.2 IPS |
|
|
Text Classification (F32)
|
100% |
939
1.35 KIPS |
|
|
Text Classification (F16)
|
100% |
874
1.26 KIPS |
|
|
Text Classification (I8)
|
92% |
561
805.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1675
30.8 IPS |
|
|
Machine Translation (F16)
|
100% |
2020
37.2 IPS |
|
|
Machine Translation (I8)
|
64% |
972
17.9 IPS |
